Defence of the Master's thesis in Tallinn University of Technology. (Computer Systems Design)

1. Master’s Thesis
Tallinn University of Technology
Department of Computer Engineering
Computer Systems Design
DECISION SUPPORT
SYSTEM FOR
FINANCIAL LIQUIDITY
PLANNING
Author: Erik Kaju
Supervisor: Tarmo Robal (PhD)
15.06.2015

2. THE OBJECTIVE
The objective of this thesis is to use information
technology facilities and build a minimum viable
product solution that would potentially enhance a
liquidity planning process in the world’s fastest
growing money transfer service.
2

3. TRANSFERWISE

4. TRANSFERWISE
TransferWise (TW) is an
international money
transfer platform.
It makes it up to 10
times cheaper to send
money abroad
compared to using
similar services offered
by banks.
TW’s technology is
based on peer-to-peer
system and has helped
customers to move
more than £4,5bn – an
approach that has
saved customers
£180m.
4

5. THE PROBLEM
IMBALANCE OF OF CURRENCY FLOWS
5

6. DIFFICULTY OF FORECASTING
6
DIVERSITY OF
FACTORS
THAT
INFLUENCE
THE DEMAND
FOR MONEY
RAPIDLY
CHANGING
ENVIRONMENT
RANDOMNESS

7. FACTORS ANALYSIS
INTERNAL
• Liquidity buffer account balance
• Suspended transfers
• Liquidity in transit
7
EXTERNAL
• Recent volume descriptor
• Growth trends
• Weekly patterns
• Monthly patterns
• Exchange rate movements
• Frequency of extra large payments
• National holidays

8. WEEKLY PATTERNS
8

9. MONTHLY PATTERNS
9

10. TIME SERIES ANALYSIS
A time series is a collection of observations of well-defined data
items obtained through repeated measurements over time.

11. COMPUTATIONAL MODEL

12. WEEKLY PATTERNS
12

13. MONTHLY PATTERNS
13

14. VISUALISATIONS
14

15. FORECASTING ALGORITHM
15

16. LIQUIDITY RECONCILIATION
DECISION SUPPORT SYSTEM

17. THE IMPLEMENTATION
17
GRAILSGROOVYJAVA

18. THE PROTOTYPE
18

19. THE PROTOTYPE
19

20. THE PROTOTYPE
20

21. TESTING
21

22. TESTING, RESULTS
22

23. THE OUTCOME
23
THE PROPOSED NEXT STEPS
1. Include more factors into
calculational model
2. Enhance the proposal
algorithm
3. Carry out tests and compare
the efficiency vs. current
human factor
4. Based on results decide
whether more determinants
need implementing
5. If needed, repeat steps 1,2,3
6. Go live
7. Continuously improve the
solution
PLAN:
WHAT TO
DO NEXT

24. THANK YOU
24

25. QUESTION FROM REVIEWER
Q:
Kuidas suhtute mõttesse, eemaldada andmetest põhitrendid ja siis katsetada jääki
juhuslikkusele ja alles seejärel tuua sisse lisafaktoreid?
How do you find the idea of removing main trends from data and test the irregular
component and only then introduce extra factors. (perform seasonal adjustment)?
A:
Aegridade teooria järgi oleks selline lähenemine õige, aga kuna seadsin antud tööle järgneva
tuleviku väljavaateks just olulisemate ettevõtteväliste ja sisemiste sesoonsusest sõltumatute
lisafaktorite mõju uurimise ja vähendamise, siis põhitrendide analüüsi jätsin teadlikult kõrvale.
According to the theory of time series, such approach is correct. I have set a goal for future
development after this thesis to mitigate the impact of main internal and external determinants that
are independent from seasonalities. For that reason I decided not to perform classical seasonal
adjustment.
25
Reviewer: Enn Õunapuu